Source and mask optimization by changing intensity and shape of the illumination source and magnitude and phase of mask diffraction orders

ABSTRACT

An illumination source is optimized by changing the intensity and shape of the illumination source to form an image in the image plane that maximizes the minimum ILS at user selected fragmentation points while forcing the intensity at the fragmentation points to be within a small intensity range. An optimum mask may be determined by changing the magnitude and phase of the diffraction orders to form an image in the image plane that maximizes the minimum ILS at user selected fragmentation points while forcing the intensity at the fragmentation points to be within a small intensity range. Primitive rectangles having a size set to a minimum feature size of a mask maker are assigned to the located minimum and maximum transmission areas ad centered at a desired location. The edges of the primitive rectangle are varied to match optimal diffraction orders O(m,n). The optimal CPL mask O CPL (x,y) is then formed.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.12/962,522, filed Dec. 7, 2010, (Now U.S. Pat. No. 8,730,452), which isa Divisional of U.S. patent application Ser. No. 12/186,410, filed Aug.5, 2008, (Now U.S. Pat. No. 7,864,301), which is a Divisional of U.S.patent application Ser. No. 10/813,626, filed Mar. 31, 2004,(Abandoned), which claims the benefit of U.S. Provisional PatentApplication Ser. No. 60/458,365, filed Mar. 31, 2003, each of which ishereby incorporated by reference in its entirety.

BACKGROUND

The field of the invention relates generally to a method and programproduct for optimizing illumination source and mask features formicrolithography. Lithographic apparatus can be used, for example, inthe manufacture of integrated circuits (ICs). In such a case, thephotolithographic mask may contain a circuit pattern corresponding to anindividual layer of the IC, and this pattern can be imaged onto a targetportion (e.g. comprising one or more dies) on a substrate (siliconwafer) that has been coated with a layer of radiation-sensitive material(resist). In general, a single wafer will contain a whole network ofadjacent target portions that are successively irradiated via theprojection system, one at a time. In one type of lithographic projectionapparatus, each target portion is irradiated by exposing the entire maskpattern onto the target portion in one go; such an apparatus is commonlyreferred to as a wafer stepper. In an alternative apparatus, commonlyreferred to as a step-and-scan apparatus, each target portion isirradiated by progressively scanning the mask pattern under theprojection beam in a given reference direction (the “scanning”direction) while synchronously scanning the substrate table parallel oranti-parallel to this direction. Since, in general, the projectionsystem will have a magnification factor M (generally <1), the speed V atwhich the substrate table is scanned will be a factor M times that atwhich the mask table is scanned. More information with regard tolithographic devices as described herein can be gleaned, for example,from U.S. Pat. No. 6,046,792, incorporated herein by reference.

In a manufacturing process using a lithographic projection apparatus, amask pattern is imaged onto a substrate that is at least partiallycovered by a layer of radiation-sensitive material (resist). Prior tothis imaging step, the substrate may undergo various procedures, such aspriming, resist coating and a soft bake. After exposure, the substratemay be subjected to other procedures, such as a post-exposure bake(PEB), development, a hard bake and measurement/inspection of the imagedfeatures. This array of procedures is used as a basis to pattern anindividual layer of a device, e.g. an IC. Such a patterned layer maythen undergo various processes such as etching, ion-implantation(doping), metallization, oxidation, chemo-mechanical polishing, etc.,all intended to finish off an individual layer. If several layers arerequired, then the whole procedure, or a variant thereof, will have tobe repeated for each new layer. Eventually, an array of devices will bepresent on the substrate (wafer). These devices are then separated fromone another by a technique such as dicing or sawing, whence theindividual devices can be mounted on a carrier, connected to pins, etc.Further information regarding such processes can be obtained, forexample, from the book Microchip Fabrication: A Practical Guide toSemiconductor Processing, Third Edition, by Peter van Zant, McGraw HillPublishing Co., 1997, ISBN 0-07-067250-4, incorporated herein byreference.

For the sake of simplicity, the projection system may hereinafter bereferred to as the “lens”; however, this term should be broadlyinterpreted as encompassing various types of projection systems,including refractive optics, reflective optics, and catadioptricsystems, for example. The radiation system may also include componentsoperating according to any of these design types for directing, shapingor controlling the projection beam of radiation, and such components mayalso be referred to below, collectively or singularly, as a “lens”.Further, the lithographic apparatus may be of a type having two or moresubstrate tables (and/or two or more mask tables). In such “multiplestage” devices the additional tables may be used in parallel, orpreparatory steps may be carried out on one or more tables while one ormore other tables are being used for exposures. Twin stage lithographicapparatus are described, for example, in U.S. Pat. No. 5,969,441 and WO98/40791, incorporated herein by reference.

The photolithographic masks referred to above comprise geometricpatterns corresponding to the circuit components to be integrated onto asilicon wafer. The patterns used to create such masks are generatedutilizing CAD (computer-aided design) programs, this process is oftenbeing referred to as EDA (electronic design automation). Most CADprograms follow a set of predetermined design rules in order to createfunctional masks. These rules are set by processing and designlimitations. For example, design rules define the space tolerancebetween circuit devices (such as gates, capacitors, etc.) orinterconnect lines, so as to ensure that the circuit devices or lines donot interact with one another in an undesirable way. The design rulelimitations are typically referred to as “critical dimensions” (CD). Acritical dimension of a circuit can be defined as the smallest width ofa line or hole or the smallest space between two lines or two holes.Thus, the CD determines the overall size and density of the designedcircuit.

Various techniques exist to achieve illumination optimization forphotolithography. Various mask optimization techniques also have beenknown. However, currently illumination optimization and maskoptimization are not generally linked. U.S. Pat. No. 6,563,566 toRosenbluth et al. discloses to perform illumination optimization andmask optimization through a series of calculations which attempt tolinearize the optimization of the mask transmission. Rosenbluthdiscloses to maximize the minimum NILS (normalized image log slope) andto select various constraints to be used in the calculations. Rosenbluthalso recognizes that the calculations may be limited relying on thesymmetry of a mask. However, the linearization of the mask transmissionused by Rosenbluth requires using several approximations in thecalculations, instead of the actual imaging equations themselves, whichproduce errors in implementing a mask to form a desired image. Thelinearization of the mask transmission also requires the use of asignificant number of variables, which requires significant computationtime to perform the calculations.

As logic feature sizes decrease, there is a need to provide maskimplementations that precisely form a desired image with minimumcomputational time.

SUMMARY OF THE INVENTION

In accordance with the present invention, a method for optimizing anillumination source for a mask illumination may comprise the steps of:providing illumination from an illumination source to a plurality ofsource points and a predetermined mask pattern; selecting fragmentationpoints in an image plane of an image formed by the illumination providedto the predetermined mask pattern; determining an intensity and imagelog slope of illumination at each fragmentation point; determining anoptimal illumination source as an illumination source which maximizesthe image log slope at the selected fragmentation points and has anintensity within a predetermined range.

In accordance with the present invention, a method for determining anoptimal mask may comprise the steps of: determining optimum diffractionorders of an ideal mask; obtaining an optimal transmission mask based onthe optimized diffraction orders of the ideal mask; and determining anoptimal mask based on the optimal transmission mask, wherein the optimumdiffraction orders of the ideal mask are determined by determining amagnitude and phase of diffraction orders which form an image in animage plane which maximizes the minimum illumination log slope at userselected fragmentation points while forcing an intensity of illuminationat the fragmentation points to be within a predetermined range.

In accordance with the present invention, a method of obtaining anoptimum source and an optimum mask may comprise the steps of: providingillumination from an illumination source to a plurality of source pointsand a predetermined mask pattern; selecting fragmentation points in animage plane of an image formed by the illumination provided to thepredetermined mask pattern; determining an intensity and image log slopeof illumination at each fragmentation point; and simultaneously changingthe intensity and shape of the illumination source and the magnitude andphase of diffraction orders of the mask to form an image in the imageplane that maximizes the minimum image log slope at the fragmentationpoints while forcing the intensity at the fragmentation points to bewithin a predetermined intensity range.

In accordance with the present invention, a method of optimizing aplacement of transmission and phase shifting features on a mask maycomprise the steps of: obtaining optimal mask transmissioncharacteristics based on optimum diffraction orders of the mask;locating areas of maximum transmission and minimum transmission;assigning a primitive area as an area centered on an area of maximumtransmission or minimum transmission; varying edges of each primitivearea to match optimal diffraction orders, wherein each primitive areahas a minimum size which is substantially equal to a minimum featuresize of the mask.

In a method of the present invention, the step of obtaining optimal masktransmission characteristics may include a step of determininghorizontal diffraction orders of an optimum mask, wherein the number ofhorizontal diffraction orders is determined according to the equation:

$n = {{2\; {{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where m is the number of horizontal diffraction orders; λ is awavelength of the illumination source; NA is a numerical aperture of theprojection optics; and σ_(max) is a radial extent of the distribution ofa beam of light from the illumination source.

In a method of the present invention, the step of obtaining optimal masktransmission characteristics may include a step of determining verticaldiffraction orders of an optimum mask, wherein the number of verticaldiffraction orders is determined according to the equation:

$n = {{2\; {{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where n is the number of vertical diffraction orders; λ is a wavelengthof the illumination source; NA is a numerical aperture of the projectionoptics; and σ_(max) is a radial extent of the distribution of a beam oflight from the illumination source.

In accordance with the present invention a computer readable medium maycontain instructions for a computer to perform a method for optimizingan illumination source for a mask illumination which may comprise thesteps: of providing illumination from an illumination source to aplurality of source points and a predetermined mask pattern; selectingfragmentation points in an image plane of an image formed by theillumination provided to the predetermined mask pattern; determining anintensity and image log slope of illumination at each fragmentationpoint; determining an optimal illumination source as an illuminationsource which maximizes the image log slope at the selected fragmentationpoints and has an intensity within a predetermined range.

In accordance with the present invention a computer readable medium maycontain instructions for a computer to cause performance of a method fordetermining an optimal mask which may comprise the steps of: determiningoptimum diffraction orders of an ideal mask; obtaining an optimaltransmission mask based on the optimized diffraction orders of the idealmask; and determining an optimal mask based on the optimal transmissionmask, wherein the optimum diffraction orders of the ideal mask aredetermined by determining a magnitude and phase of diffraction orderswhich form an image in an image plane which maximizes the minimumillumination log slope at user selected fragmentation points whileforcing an intensity of illumination at the fragmentation points to bewithin a predetermined range.

In accordance with the present invention a computer readable medium maycontain instructions for a computer to cause performance of a method ofobtaining an optimum source and an optimum mask which may comprise thesteps of providing illumination from an illumination source to aplurality of source points and a predetermined mask pattern; selectingfragmentation points in an image plane of an image formed by theillumination provided to the predetermined mask pattern; determining anintensity and image log slope of illumination at each fragmentationpoint; and simultaneously changing the intensity and shape of theillumination source and the magnitude and phase of diffraction orders ofthe mask to form an image in the image plane that maximizes the minimumimage log slope at the fragmentation points while forcing the intensityat the fragmentation points to be within a predetermined intensityrange.

In accordance with the present invention a computer readable medium maycontain instructions for a computer to cause performance of a method ofoptimizing a placement of transmission and phase shifting features on amask which may comprise the steps of: obtaining optimal masktransmission characteristics based on optimum diffraction orders of themask; locating areas of maximum transmission and minimum transmission;assigning a primitive area as an area centered on an area of maximumtransmission or minimum transmission; varying edges of each primitivearea to match optimal diffraction orders, wherein each primitive areahas a minimum size which is substantially equal to a minimum featuresize of the mask.

In accordance with the present invention a computer readable medium maycontain instructions for a computer to cause optimizing a placement oftransmission and phase shifting features on a mask comprising the stepsof: obtaining optimal mask transmission characteristics; locating areasof minimum transmission; assigning a primitive area as an area centeredon an area of minimum transmission; and varying edges of the primitivearea to match optimal diffraction orders, wherein the primitive area hasa minimum size which is substantially equal to a minimum feature size ofthe mask.

A computer readable medium may further contain instructions for acomputer to cause the steps of: locating an area of maximumtransmission; assigning a transmission primitive area as an areacentered on an area of maximum transmission; varying edges of thetransmission primitive area to match optimal diffraction orders, whereinthe transmission primitive area has a minimum size which issubstantially equal to a minimum feature size of the mask.

In a computer readable medium of the present invention, the step ofobtaining optimal mask transmission characteristics may include a stepof determining horizontal diffraction orders of an optimum mask, whereinthe number of horizontal diffraction orders is determined according tothe equation:

$m = {{2\; {{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where m is the number of horizontal diffraction orders; λ is awavelength of the illumination source; NA is a numerical aperture of theprojection optics; and σ_(max) is a radial extent of the distribution ofa beam of light from the illumination source.

In a computer readable medium of the present invention, the step ofobtaining optimal mask transmission characteristics may include a stepof determining vertical diffraction orders of an optimum mask, whereinthe number of vertical diffraction orders is determined according to theequation:

$n = {{2\; {{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where n is the number of vertical diffraction orders; λ is a wavelengthof the illumination source; NA is a numerical aperture of the projectionoptics; and σ_(max) is a radial extent of the distribution of a beam oflight from the illumination source.

In accordance with the present invention, an apparatus for optimizing anillumination source for a mask illumination may comprise: an input unitwhich inputs characteristics of an illumination device; and a processingunit which is configured to change an intensity and shape of anillumination to form an image in an image plane that maximizes theminimum image log slope at user selected fragmentation points.

In accordance with the present invention, an apparatus for optimizing amask may comprise: an input unit which inputs a desired image pattern;and a processing unit which is configured to change a magnitude andphase of diffraction orders to form an image in the image plane thatmaximizes the minimum image log slope at user selected fragmentationpoints while forcing the intensity at the fragmentation points to bewithin a predetermined intensity range.

In accordance with the present invention, an apparatus for obtaining anoptimum source and an optimum mask may comprise: an input unit whichaccepts user inputs; and a processing unit configured to simultaneouslychange an intensity and shape of an illumination source and change amagnitude and phase of diffraction orders to form an image in an imageplane which maximizes a minimum image log slope at user selectedfragmentation points while forcing an intensity at the fragmentationpoints to be within a predetermined intensity range.

In accordance with the present invention, an apparatus for optimizing aplacement of transmission and phase shifting features on a maskcomprising: an input unit which inputs characteristics of anillumination device; and a processing unit which is configured to obtainoptimal mask transmission characteristics based on optimum diffractionorders of the mask, locate areas of minimum transmission and maximumtransmission, assign primitive areas as areas centered on an area ofminimum transmission or an area of maximum transmission, and vary edgesof the primitive area to match optimal diffraction orders, wherein theprimitive areas have a minimum size which is substantially equal to aminimum feature size of the mask.

In an apparatus of the present invention, the optimal mask transmissioncharacteristics may include horizontal diffraction orders of an optimummask, and the number of horizontal diffraction orders is determinedaccording to the equation:

$m = {{2\; {{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where m is the number of horizontal diffraction orders; λ is awavelength of the illumination source; NA is a numerical aperture of theprojection optics; and σ_(max) is a radial extent of the distribution ofa beam of light from the illumination source.

In an apparatus of the present invention, the optimal mask transmissioncharacteristics may include vertical diffraction orders of an optimummask, wherein the number of vertical diffraction orders is determinedaccording to the equation:

$n = {{2\; {{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}$

where n is the number of vertical diffraction orders; λ is a wavelengthof the illumination source; NA is a numerical aperture of the projectionoptics; and σ_(max) is a radial extent of the distribution of a beam oflight from the illumination source.

The present invention provides an advantage of a fast computation ofmask parameters by limiting the number of mask optimization variablesconsidered. The number of illumination optimization variables may bereduced by relying on the mask symmetry. The number of mask optimizationvariables may also be reduced by optimizing the diffraction orders ofthe mask rather than performing computations with the mask transmission.Optimization of the mask diffraction orders is a non-linear process;hence, reducing the number of variables decreases computation time.Furthermore the mask transmission is optimized by performing anon-linear optimization of the diffraction orders followed by a linearoptimization of selecting quantized mask transmissions to equal theoptimal diffraction orders.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and form a part ofthe specification, together with the description serve to explain theprinciples of the invention. In the drawings:

FIGS. 1A and 1B illustrate an exemplary illumination using Abbe imagingaccording to the present invention;

FIG. 2 illustrates an exemplary process for obtaining illuminationoptimization according to the present invention;

FIG. 3 provides a graphical representation of the generation oftransmission cross coefficients (TCC) according to the presentinvention;

FIG. 4 illustrates an exemplary process for performing a maskoptimization according to the present invention;

FIGS. 5A and 5B illustrate additional mask constraints that may beconsidered in optimizing a mask according to the present invention;

FIG. 6 illustrates an exemplary process for converting an optimaltransmission mask to a CPL mask according to the present invention;

FIG. 7A illustrates an exemplary DRAM mask pattern and FIG. 7Billustrates an optimum illumination source used with the mask pattern ofFIG. 7A;

FIGS. 8A-8C illustrate diffraction orders of various masks to illustratethe diffraction orders of a CPL mask in accordance with the presentinvention;

FIGS. 9A-9C illustrate the application of the optimal illumination to anoptimal mask (FIG. 9A);

FIGS. 10A and 10B illustrate aerial image comparisons between a CPL maskand an 8% AttPSM (phase shifted mask);

FIGS. 11A and 11B illustrate aerial image comparisons between a CPL maskand an 8% AttPSM using hexapole and annular illumination, respectively;

FIG. 12A illustrates an exemplary “Short Brickwall” pattern and FIG. 12Billustrates an illumination source which has been optimized to producethe pattern according to the principles of the present invention;

FIGS. 13A-C illustrate the diffraction orders of the exemplary mask inFIG. 12A;

FIGS. 14A-D illustrate the use of primitive edges to create an optimalmask according to the principles of the present invention;

FIGS. 15A and 15B illustrate aerial image comparisons using the ShortBrickwall pattern of FIG. 12A in a CPL mask and an AttPSM mask;

FIGS. 16A and 16B illustrate the trade-off between obtaining an optimaltransmission and using a CPL mask;

FIGS. 17A and 17B illustrate aerial image comparisons between an 8%AttPSM exposed with a dipole illumination in the top row and an annularillumination in the bottom row;

FIG. 18A illustrate the principles of the present invention as appliedto a rectangular contact array mask and FIG. 18B illustrates anillumination source which has been optimized to illuminate the patternof FIG. 18A in accordance with the present invention;

FIGS. 19A-C illustrate the diffraction orders of the exemplary mask inFIG. 18A;

FIGS. 20A-C illustrate the use of primitive edges to create a quantizedCPL mask according to the principles of the present invention;

FIGS. 21A and 21B illustrate an aerial image comparison using therectangular contact array mask of FIG. 19A;

FIGS. 22A and 22B illustrate the trade-off between obtaining an optimaltransmission and using a CPL mask;

FIGS. 23A and 23B illustrate aerial image comparisons between an 8%AttPSM exposed with dipole illumination in the top row and annularillumination in the bottom row;

FIG. 24A illustrates a Staggered Rectangular Contact Array and FIG. 24Billustrates and an illumination source which has been optimized toproduce the pattern according to the principles of the presentinvention;

FIGS. 25A-C illustrate the diffraction orders of the exemplary mask inFIG. 24A;

FIGS. 26A-C illustrate the use of primitive edges to create a quantizedCPL mask according to the principles of the present invention;

FIGS. 27A and 27B illustrate aerial image comparisons using a CPL maskand an AttPSM mask;

FIGS. 28A and 28B illustrate the trade-off between obtaining an optimaltransmission and using a CPL mask;

FIGS. 29A and 29B illustrate aerial image comparisons between an 8%AttPSM exposed with quad in the top row and annular illumination in thebottom row;

FIG. 30 schematically depicts a lithographic projection apparatussuitable for use with a mask designed with the aid of the currentinvention; and

FIG. 31 illustrates an exemplary mask optimization processing unit inaccordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

Disclosed is a method for optimizing the illumination source and themask for creating a desired pattern in the image plane. In a preferredimplementation, an image is formed in the image plane with the highestimage log slope (ILS) in the optimization process at user selectedfragmentation points. The image may be optimized by changing theintensity and shape of the illumination source and by changing themagnitude and phase of the diffraction orders. In a preferredimplementation, the illumination source is first optimized and then themask diffraction orders are optimized; however, the illumination sourceand mask diffraction orders can be optimized simultaneously.

Since the ILS is a non-linear quantity, the optimization of theillumination source and the mask is a non-linear optimization. Those ofskill in the art appreciate that in a non-linear optimization thecomputational time is a function (e.g. a geometric function) of thenumber of variables. Therefore to speed the computational time, thenumber of variables must be minimized. In the illumination sourceoptimization, in accordance with the invention, the number of variablesmay be reduced by taking advantage of the symmetry of mask. For example,if the mask is symmetric with respect to the vertical and horizontalaxes, the illumination source will be symmetric with respect to thevertical and horizontal axes, allowing optimization to be achieved usinga quarter of the illumination source.

In the mask optimization in accordance with the invention, the number ofvariables may be reduced by performing an optimization of thediffraction orders in the spatial frequency domain. The maskoptimization is preferably performed in the spatial frequency domainrather than the spatial domain because the lens (e.g. the entrance pupilof the projection optics) and illumination source limit the number ofdiffraction orders which are used to form the projected image. Inaddition to optimizing the ILS at user selected fragmentation points,the shape of the image formed by the mask must match the desiredpattern. The matching is preferably done by adding a constraint thatintensity at all of the fragmentation points are the same or within apredetermined range of deviation of each other, e.g. a ±2% deviation.Preferably, after optimizing the mask diffraction orders, the optimalmask transmission may be calculated by taking the inverse Fouriertransform of the mask diffraction orders.

In the optimal mask transmission, the electric field transmission has acontinuous magnitude from 0 to 1 and a continuous phase from −180degrees to +180 degrees. Since the mask has a limited number of electricfield transmissions, the optimal transmission is preferably quantized bythe limited number of transmissions. This quantization is preferablydone by selecting quantized mask transmission areas such that thediffraction orders of the quantized mask substantially equal the optimaldiffraction orders. Because the Fourier transform is a linearcalculation, selecting quantized mask transmission areas such that thequantized mask diffraction orders equal the optimal diffractions is alinear process that can be calculated quickly.

FIGS. 1A and 1B illustrate an illumination process using Abbe imaging.As illustrated in FIG. 1A, each source point 10 may be illuminated byselectively positioning an illumination source (not shown) at thedesired source points 10. The total image intensity is the summation ofthe intensity from each of the individual source points 10. Theillumination patterns are real (in a mathematical sense), hence, theillumination must have even symmetry. Preferably, the source points arechosen to enhance the normalized image log slope (NILS) at fragmentationpoints on the image plane. A fragmentation point is commonly known to bea point on the image plane which is smaller than λ/2NA.

FIG. 1B illustrates the use of the illumination source with a typicalDRAM mask pattern (referred to as a “Brickwall”). FIG. 7A illustrates a“Long Brickwall” pattern that may be used. In FIG. 1B, portions of theresulting image are shown from illuminating a Brickwall pattern on amask of a 190 nm pitch with an illumination of λ/800 with a numericalaperture (NA) at the entrance pupil of the projection optics at 0.8. Ascan be seen in FIG. 1B, the light areas represent an image intensitythat enhances the NILS while the dark areas represent an image intensitythat degrades the NILS. The illumination source points that provide thebest result, e.g. provide the most enhanced NILS, are preferablyselected to optimize the shape of the illumination source.

An exemplary process for performing the illumination source optimizationis illustrated in FIG. 2. The illumination source optimization in thisprocess is preferably linear with non-linear constraints. Preferably,the mask transmission magnitude and phase is optimized according to thepresent invention.

As illustrated in step S1 of FIG. 2, the user preferably specifies theselected cell (e.g. region on the desired pattern) and the fragmentationpoints (x,y) (see FIG. 9A) to be evaluated. In the process, illustratedin step S2, a microprocessor preferably calculates the intensity and theNILS at each illuminator point (α,β) and at each fragmentation point(x,y), i.e., the microprocessor calculates I(α,β; x,y) and NILS(α,β;x,y). As also illustrated in step S3 of FIG. 2, the microprocessorutilizes specifications of the illumination system, such as anillumination system from Zeiss (identified as “Zeiss Specs” in FIG. 2),to perform a Gaussian convolution, to determine the minimum pupil fill(e.g., 10%), the minimum ring width (e.g. 0.2) and to force theintensity to a predetermined value. An optimization process isillustrated in step S4, in which illumination points (α,β) that maximizethe minimum NILS at each fragmentation point (x,y) are selected. Asillustrated in step S5, the intensity I(α,β; x,y) and NILS(α,β; x,y) ateach illumination point and each fragmentation point are preferablysummed with the selected illumination points that maximize the minimumNILS at each fragmentation point. The optimal illumination source tomaximize the NILS at each fragmentation point (x,y) at a desiredintensity is determined, as illustrated by step S6.

Accordingly, in the preferred implementation of the process in FIG. 2,discussed above, the intensity and shape of the illumination may bechanged to form an image in the image plane that maximizes the minimumILS at user selected fragmentation points while forcing the intensity atthe fragmentation points to be within a predetermined intensity range.

FIG. 3 illustrates an exemplary mask optimization process according tothe present invention. A technique known as Hopkins Imaging may be used,in which the log slope is attempted to be maximized by changing thepupil to maximize the NILS. Those of skill in the art will appreciatethat Abbe Imaging may also be used. Those of skill in the art appreciatethat in Abbe Imaging, an image is created for each point and the imagesare added up and integrated over the source last. Abbe Imaging isgenerally considered to be spatially incoherent. Those of skill in theart appreciate that in Hopkins Imaging the integration is over thesource first and a transfer function is obtained. It may be easier toobtain a mask optimization once from the transmission cross coefficients(TCC) and describe the entire scanner and stepper optics. For maskoptimization, the Eigen values decay rapidly to represent the TCC with afew Eigen functions. This speeds computation time.

FIG. 3 also illustrates the creation of the TCC using Hopkins imaging.The TCC is an autocorrelation of the illumination pupil with theprojection pupil. FIG. 3 illustrates the autocorrection of theillumination pupil centered at (0,0) with the projection pupil centeredat

$\frac{m\; \lambda}{P_{x}N\; A},\frac{n\; \lambda}{P_{y}N\; A}$

and with the complex conjugate of the projection pupil centered at

$\frac{p\; \lambda}{P_{x}N\; A},\frac{q\; \lambda}{P_{y}N\; A},$

where NA represents the numerical aperture of the projection optics, andλ represents the wavelength of the illumination source.

In performing the Hopkins Imaging, the integration occurs over thesource first to form the image transfer cross coefficients (TCC),illustrated as TCC(m, n, p, q) in FIG. 3. The TCC is an autocorrelationof the illumination pupil with the projection pupil and is a fourdimensional (4-D) function. The next step is to diagonalize the TCC toreduce the problem to a sum of two dimensional functions. These twodimensional functions are a set of orthogonal eigenfunctions in whicheach eigenfunction is weighted by the eigenvalue, i.e., eigenfunctionswith higher eigenvalues have a larger impact on the image. Theseeigenfunctions form a set of image kernels which are used in thecalculation of the image in the object plane. The diagonalizationoperation may be performed by any known functions, such as singularvalue decomposition used in NTI Nanosurfer, or in MG Calibre. Those ofskill in the art will also appreciate that a calibrated MT Kernel canalso be used.

FIG. 4 illustrates an exemplary process for performing a maskoptimization according to the present invention to obtain anideal/optimum mask. Ideal mask transmission optimization is non-linear,however the conversion of the ideal mask transmission to a CPL maskimplementation is a linear process. In the process illustrated in FIG.4, the ideal mask is optimized in the frequency domain to speedconvergence since the optimization is non-linear. As illustrated in stepS21 of FIG. 4, the user selects the cell (e.g. region on the desiredpattern) and fragmentation points (x,y) to maximize the NILS and tominimize and maximize intensity. The microprocessor then calculates theTCC (m, n, p, q) (step S22), diagonolizes the TCC into N kernels λΦ(m,n)(step S23), and calculates the image intensity to each Kernel, i (stepS24). The calculation of the image intensity to each Kernel, i may beperformed according to equation 1.

I ₁(x,y)=|ℑ⁻¹{λ₁ |O(m,n)·Φ₁(m,n)|}|²  Eq. 1

In the preferred implementation, the mask transmission range is chosenfor CPL mask optimization. The transmission is allowed to be above 1 orbelow −1 because of the Gibb's phenomenon for image reconstruction afterlow pass filtering. The mask transmission range can be further modifiedfor an attenuating phase shift mask (PSM). For an attenuating PSM(AttPSM), the mask transmission manufacturable range becomesℑ⁻¹{O(m,n)}≦1.25 and ℑ⁻¹{O(m,n)}≧−1.25√{square root over (T)} where T isthe transmittance of the phase shift mask.

The microprocessor also receives optimization constraints that may beused to force intensity in the image plane to a predetermined value,minimize intensity below a predetermined value, maximize intensity abovea predetermined value, or conform with a mask manufacturabilityconstraint, as illustrated in step S27. The predetermined value ispreferably selected as the intensity which provides the highest imagelog slope (ILS). An exemplary optimization constraint, which may limitthe mask transmission to a manufacturable range, is set forth inequation 2.

ℑ⁻¹ {O(m,n)}≦1.25  Eq. 2

The microprocessor preferably performs an optimization of the masktransmissions by changing the diffraction orders of the mask O(m,n) tomaximize the NILS at the fragmentation points (x,y), as illustrated instep S25, such as by changing the magnitude and phase of the diffractionorders. The resulting diffraction orders of the optimization of step S25is summed with the calculated image intensity of each Kernel, i, asillustrated in step S26, and the ideal optimum mask diffraction ordersO(m,n) are provided, as illustrated in step S28. The inverse Fouriertransform is then performed to convert the calculations to the spatialdomain from the frequency domain, as illustrated in step S29, to obtainthe optimal transmission mask o(x,y) in the spatial domain, asillustrated in step S30.

Additional mask constraints may be considered in optimizing a mask asillustrated in FIGS. 5A and 5B. The diffraction order may be evaluatedby a real component and an imaginary component and may be represented byequation 3.

O(m,n)=O*(−m,−n)  Eq. 3

Equation 3 guarantees that the mask is real in a mathematical sense. Areal mask has transmission phases of 0° and 180°.

The number of real diffraction orders, x, may be characterized byequation 4.

$\begin{matrix}{x = {{\frac{( {m + 1} )}{2}\frac{( {n + 1} )}{2}} + {\frac{( {m - 1} )}{2}\frac{( {n - 1} )}{2}}}} & {{Eq}.\mspace{14mu} 4}\end{matrix}$

The number of imaginary diffraction orders, y, may be characterized byequation 5.

$\begin{matrix}{y = {{\frac{( {m + 1} )}{2}\frac{( {n + 1} )}{2}} + {\frac{( {m - 1} )}{2}\frac{( {n - 1} )}{2}} - 1}} & {{Eq}.\mspace{14mu} 5}\end{matrix}$

However, a mask must be real, which restricts the number of orders tooptimize to x+y, and the entrance pupil of the projection optics limitsthe number of diffraction orders that may be used by blocking thehighest diffraction orders. Hence, the maximum number of horizontaldiffraction orders that may be used, m, may be represented by equation6.

$\begin{matrix}{n = {{{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack} + 1}} & {{Eq}.\mspace{14mu} 7}\end{matrix}$

Where m is the number of horizontal diffraction orders, σ_(max) is aradial extent of the distribution of a beam of light from theillumination source, λ is a wavelength of the illumination source,P_(x), is the pitch of the repetitive cell in the x direction, and NA isa numerical aperture of the entrance pupil of the projection optics.

The number of vertical diffraction orders that may be used, n, may berepresented by equation 7.

$\begin{matrix}{m = {{{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack} + 1}} & {{Eq}.\mspace{14mu} 6}\end{matrix}$

where n is the number of vertical diffraction orders, σ_(max) is aradial extent of the distribution of a beam of light from theillumination source, λ is a wavelength of the illumination source,P_(y), is the pitch of the repetitive cell in the y direction, and NA isa numerical aperture of the entrance pupil of the projection optics.

In the preferred implementation, the definition for x and y of the pitchP is the axes of the Cartesian coordinate system in which the x axis isorthogonal to the y axis. However, the coordinate system can be anylinear coordinate system in which any two lines, g₁, and g₂,intersecting at an origin, describe the linear coordinate system, i.e.,g₁ and g₂, need not be necessarily orthogonal. In such a non-orthogonalcoordinate system P_(x) describes the pitch along the axis g₁ and P_(y)describes the pitch along the axis g₂.

Accordingly, in the preferred implementation of the process illustratedin FIG. 4, as discussed above, the magnitude and phase of thediffraction orders may be changed to form an image in the image planethat maximizes the minimum ILS at user selected fragmentation pointswhile forcing the intensity at the fragmentation points to be within apredetermined intensity range.

The illumination source optimization, illustrated in FIG. 2, may besimultaneously performed with the mask optimization, illustrated in FIG.4. Accordingly, the intensity and shape of the illumination and themagnitude and phase of the diffraction orders may be simultaneouslychanged to form an image in the image plane that maximizes the minimumILS at user selected fragmentation points while forcing the intensity atthe fragmentation points to be within a predetermined intensity range.

The ideal optimal transmission mask determined in the exemplary processof FIG. 4 maybe converted to be implemented in an actual mask, such as aCPL mask, as illustrated by the process illustrated in FIG. 6. As shownin step S31 in FIG. 6, an ideal optimal transmission mask, which may bedetermined according to the process illustrated in FIG. 4, is providedto be converted. In the process, a dark field mask is preferably used tostart, as illustrated in step S32. Then areas of minimum transmissionare located and assigned a −1 (step S33), and areas of maximumtransmission are also located and assigned a +1 (step S34). Primitiverectangles preferably having a size set to a minimum feature size of amask maker are assigned to the located minimum transmission areas andcentered at a desired location (step S35). Likewise, primitiverectangles are assigned for the located areas of maximum transmissionand centered (step S36). With the assigned −1 and +1 values, thediffraction orders needed for optimization start at

${- 1}*{{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}$

and end at

${+ 1}*{{{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}.}$

Hence, the maximum number of horizontal diffraction orders that may beused, m, may be represented by the equation:

$\begin{matrix}{m = {{2\; {{floor}\;\lbrack \frac{{P_{x}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}} & {{Eq}.\mspace{14mu} 8}\end{matrix}$

and the equation:

$\begin{matrix}{n = {{2\; {{floor}\;\lbrack \frac{{P_{y}( {\sigma_{\max} + 1} )}N\; A}{\lambda} \rbrack}} + 1}} & {{Eq}.\mspace{14mu} 9}\end{matrix}$

may represent the maximum number of vertical diffraction orders, n thatmay be used. As illustrated in step S37, the −1 and +1 rectangle edgesmay be varied to match optimal diffraction orders O(m,n). The optimalCPL mask O_(CPL)(x,y) may be formed as illustrated in step S38.

In the process illustrated in FIG. 6, the mask conversion is linear.However, CPL edge effects can also be taken into account by modifyingthe diffraction order through a perturbational model. In theperturbational model, edges of the mask are replaced with local areasthat have transmission of neither 0, +1, or −1. These areas allow ascalar mask to emulate the vector edge effects from a CPL mask. Those ofskill in the art will appreciate that many perturbational models may beused, such as those disclosed by J. Tirapu-Azpiroz, E. Yablonovitch,“Fast evaluation of Photomask, Near-Fields in Sub-Wavelength 19311×1Lithography,” Proc of the SPIE, vol. 5377 (2004), and K. Adam, A.Neureuther, “Simplified Models For Edge Transitions In Rigorous MaskModeling,” Proc. of the SPIE, vol. 4346 (2001), pp. 331-344.

FIG. 7A illustrates an exemplary DRAM mask pattern, commonly referred toas a Long Brickwall. FIG. 7B illustrates an optimum illumination sourcefor the mask of FIG. 7A obtained according to the principles of thepresent invention. The illumination source and CPL mask are optimizedfor λ/800, NA=0.8 and 190 nm pitch (k1=0.306). The source illuminationwas optimized for the long brickwall using the algorithm outlined inFIG. 2. The illumination poles on the y axis help improve the NILS atthe end of the long brick while the illumination poles on the x axishelp improve the NILS in between the bricks.

FIGS. 8A-8C illustrate diffraction orders of various masks. FIG. 8Aillustrates the original diffraction orders of the mask utilizingAttPSM. FIG. 8B illustrates the ideal optimal diffraction ordersdetermined according to the process illustrated in FIG. 4 of the presentinvention. FIG. 8C illustrates the implementation of the optimaldiffraction orders with a CPL mask, according to the process illustratedin FIG. 6 of the present invention. The optimal diffraction orders forcemore energy into the higher orders (±2,0) and (±1,±3). Those of skill inthe art will appreciate that a CPL mask can represent the optimaldiffraction orders almost identically.

FIGS. 9A-9C illustrate the application of the optimal illumination to anoptimal mask (FIG. 9A). In FIG. 9A the “*” points identify the NILSoptimization points, the “+” points identify the points at whichintensity should be maximized, and the “−” points identify the points atwhich intensity should be minimized. The NILS optimization attempts tomake the slope of the intensity at the image plane as large as possibleto obtain a high contrast in printing the mask features. The NILS ispreferably within a set value which is suitable for the determined NILSoptimization points along a mask feature. Those of skill in the art willappreciate that a CPL mask has three phase values, +180, 0 and −180degrees. The CPL mask illustrated in FIG. 8C is formed by quantizing theoptimal mask transmission, to form a quantized CPL mask transmission.

FIGS. 10A and 10B and 11A and 11B illustrate aerial image comparisonsbetween a CPL mask and an 8% AttPSM (attenuated phase shifted mask). InFIG. 10A the CPL mask was exposed with hexapole illumination. In FIG.10B the PSM mask was exposed with hexapole illumination. As illustratedin FIGS. 10A and 10B, the contrast and the NILS is much better inbetween the lines with the CPL mask than the PSM mask. It can be seenthat CPL has a production worthy process margin while the 8% solution isless favorable. However, CPL has a little necking which may becorrectable by adding more optimization points.

Also, as illustrated in FIG. 11A, the hexapole illuminator for 8% AttPSM also shows NILS improvement over annular illumination shown in FIG.11B. However, a larger process margin may be gained by using CPL withthe hexapole illuminator.

Optimizing the mask in the frequency domain limits the size of theoptimization problem and speeds convergence. Reconstruction of theoptimal CPL mask from the optimal diffraction orders is a linear problemin the frequency domain. Process window improvement may be optimal withthe optimal diffraction orders for all structures, which may minimizethe effects of focus and exposure variations in the scanner and in thewafer topography. Process window, as used herein, is the amount ofexposure latitude (EL) as a function of depth of focus (DOF). Processwindow improvement with the optimal CPL may also be optimal. CPL may beused to improve the process window at a low k1 factor. The k1 factor asused herein may be defined by CD*NA/λ, where CD is the criticaldimension of the feature to be printed, and λ is the wavelength of theillumination source. Additionally, illumination optimization does notneed to run first. Using the present invention the mask can be optimizedto an existing OAI (quasar, cquad (a quadrupole illuminator with poleson the Cartesian x and y axes, such as a quasar illuminator rotated 45degrees), annular illumination). Also, in the present invention, themask can be optimized for a single or double exposure (1 or 2 masks) orfor a 2 tone mask (binary or AttPSM). Most ideal transmission masks canbe represented with CPL in accordance with the present invention.

FIGS. 12A and 12B illustrate an exemplary “Short Brickwall” pattern inwhich the source and the CPL mask have been optimized according to theprinciples of the present invention. FIG. 12B illustrates an optimumillumination source for the pattern of FIG. 12A which has been obtainedaccording to the principles of the present invention as illustrated inFIG. 2. The source and the CPL mask were optimized for λ/800 NA=0.8 and190 nm pitch. Once again, the contrast and the NILS can be observed.

FIGS. 13A-C illustrate the diffraction orders of the exemplary mask inFIG. 12A. FIG. 13A illustrates the original diffraction order with theAttPSM mask, FIG. 13B illustrates the ideal optimal diffraction ordersdetermined according to the process illustrated in FIG. 4 of the presentinvention. FIG. 13C illustrates an implementation of the optimaldiffraction orders with a CPL mask according to the process illustratedin FIG. 4 of the present invention. Those of skill in the art willappreciate that the optimal diffraction orders force more energy into(±1,±1) areas. As illustrated by FIGS. 13B and 13C, the CPL mask canrepresent the optimal diffraction orders almost identically.

FIGS. 14A-D illustrate the use of primitive edges to create an optimalmask according to the principles of the present invention. FIG. 14Aillustrates the exemplary Short Brickwall mask of FIG. 12A. FIG. 14Billustrates the optimal mask transmission of the mask in FIG. 14A. FIG.14C illustrates using an arcuate modeling technique to map the primitiveedges more closely with the optimal mask transmission. FIG. 14Dillustrates using primitive rectangles to map the optimal masktransmission. As illustrated by FIGS. 14C and 14D, two CPLimplementations may lead to substantially the same diffraction orderspectrum. Primitive edges are not critical but using primitives may leadto a smaller figure count and possibly allow an easier inspection of themask.

FIGS. 15A-17B illustrate aerial image comparisons using the ShortBrickwall of FIG. 12A. In FIG. 15, a CPL mask and an 8% AttPSM mask areboth exposed with dipole illumination. As seen in FIGS. 15A and 15B, thecontrast and NILS is much better in between the lines and the end of theline with CPL than the PSM mask. The CPL mask has production worthyprocess margins while the 8% solution does not appear to be asfavorable. As also illustrated in FIGS. 15A and 15B, the CPL maskmaintains the area better than 8% AttPSM.

FIGS. 16A and 16B illustrate the trade-off between obtaining an optimaltransmission and using a CPL mask. As illustrated by FIGS. 16A and 16B,there is almost no difference between optimal transmission and CPLrepresentation. Hence, the CPL mask offers a favorable solution for maskoptimization according to the principles of the present invention.

FIG. 17A illustrates aerial image comparisons between an 8% AttPSMexposed with dipole illumination and FIG. 17B illustrates using annularillumination. As shown in FIGS. 17A and 17B, the NILS is better withdipole illumination in comparison to annular illumination. Annularillumination has better NILS at the end of line (EOL). However, the NILSprobably is not large enough with annular illumination to print brickswithout bridging.

FIGS. 18A-23B illustrate the principles of the present invention asapplied to a rectangular contact array mask, depicted in FIG. 18A. InFIGS. 18A and 18B, with the source and the CPL Mask optimized for λ800NA=0.8 and 190 nm pitch. Once again, the contrast and the NILS can beobserved.

FIGS. 19A-C illustrate the diffraction orders of the exemplary mask inFIG. 18A. FIG. 19A illustrates the original diffraction order with theAttPSM mask, FIG. 19B illustrates the optimal diffraction orderdetermined by the principles of the present invention, and FIG. 19Cillustrates the optimal diffraction order implemented with a CPL mask.Those of skill in the art will appreciate that the optimal diffractionorders force more energy into the higher orders (±1,0), (0,±1), and(0,±2). As illustrated by FIGS. 19B and 19C, the CPL mask can representthe optimal diffraction orders almost identically.

FIGS. 20A-C illustrate the use of primitive edges to create a quantizedCPL mask according to the principles of the present invention. FIG. 20Aillustrates the exemplary Rectangular Contact Array mask of FIG. 19A.FIG. 20B illustrates the optimal mask transmission of the mask in FIG.20A. FIG. 20C illustrates using primitive rectangles to map the optimalmask transmission to create a quantized CPL mask.

FIGS. 21A-23B illustrate aerial image comparisons using the RectangularContact Array mask of FIG. 19A. In FIG. 21A, a CPL mask and in FIG. 21Ban 8% AttPSM mask are both exposed with hexapole illumination. As seenin FIGS. 21A and 21B, the peak intensity and NILS are better with theCPL mask. The CPL mask has production worthy DOF (depth of focus) whilethe 8% AttPSM solution does not appear to have sufficient DOF to be asfavorable. As also illustrated in FIGS. 21A and 21B, the CPL maskmaintains the area better than the 8% AttPSM.

FIGS. 22A and 22B illustrate a trade-off between obtaining an optimaltransmission and using a CPL mask. As illustrated by FIGS. 22A and 22B,there appears to be a slightly better NILS with optimal transmissionreticle in comparison to CPL.

FIGS. 23A and 23B illustrate aerial image comparisons between an 8%AttPSM exposed with dipole illumination in the top row and annularillumination in the bottom row. As shown in FIGS. 23A and 23B, the peakintensity and NILS are better with hexapole illumination in comparisonto annular illumination. The peak intensity with annular illuminationmay not be sufficient to print through focus.

FIGS. 24A-29B illustrate the principles of the present invention asapplied to a Staggered Rectangular Contact Array, depicted in FIG. 24A.FIGS. 24A and 24B illustrate an exemplary Staggered Rectangular ContactArray mask in which the source and CPL mask have been optimizedaccording to the principles of the present invention. In FIGS. 24A and24B, the source and CPL Mask were optimized for λ/800, NA=0.8 and 190 nmpitch. Once again, the contrast and the NILS can be observed.

FIGS. 25A-C illustrate the diffraction orders of the exemplary mask inFIG. 24A. FIG. 25A illustrates the original diffraction order with theAttPSM mask, FIG. 25B illustrates the optimal diffraction orderdetermined by the principles of the present invention, and FIG. 25Cillustrates the optimal diffraction order with a CPL implementation.Those of skill in the art will appreciate that the optimal diffractionorders force more energy into (0,±2) and (±1,±1) areas. As illustratedby FIGS. 25B and 25C, the CPL mask can represent the optimal diffractionorders almost identically.

FIGS. 26A-C illustrate the use of primitive edges to create a quantizedCPL mask according to the principles of the present invention. FIG. 26Aillustrates the exemplary Staggered Rectangular Contact Array mask ofFIG. 24A. FIG. 26B illustrates the optimal mask transmission of the maskin FIG. 24A. FIG. 26C illustrates using primitive rectangles to map theoptimal mask transmission to create a quantized CPL mask. In FIGS.26A-C, 180 degree outriggers may be used at the sides of the contactarray.

FIGS. 27A-29B illustrate aerial image comparisons using the RectangularContact Array mask of FIG. 24A. In FIGS. 27A and 27B, a CPL mask and an8% AttPSM, respectively, mask are both exposed with quad illumination.As seen in FIGS. 27A and 27B, the peak intensity and NILS are betterwith the CPL mask than the PSM mask. The CPL mask also has a greaterexposure latitude and DOF in comparison to the 8% AttPSM mask.

FIGS. 28A and 28B illustrate the trade-off between obtaining an optimaltransmission and using a CPL mask. As illustrated by FIGS. 28A and 28B,there is almost no difference between optimal transmission and the CPLmask representation. The CPL mask offers a favorable solution for maskoptimization according to the principles of the present invention.

FIGS. 29A and 29B illustrate aerial image comparisons between an 8%AttPSM exposed with quad illumination in the top row and annularillumination in the bottom row. As shown in FIGS. 29A and 29B, the peakintensity and NILS are better with quad illumination than annularillumination. The peak intensity with annular illumination may not besufficient to print through focus.

FIG. 30 schematically depicts a lithographic projection apparatussuitable for use with a mask designed with the aid of the currentinvention. The apparatus comprises:

-   -   a radiation system Ex, IL, for supplying a projection beam PB of        radiation. In this particular case, the radiation system also        comprises a radiation source LA;    -   a first object table (mask table) MT provided with a mask holder        for holding a mask MA (e.g. a reticle), and connected to first        positioning means for accurately positioning the mask with        respect to item PL;    -   a second object table (substrate table) WT provided with a        substrate holder for holding a substrate W (e.g. a resist-coated        silicon wafer), and connected to second positioning means for        accurately positioning the substrate with respect to item PL;    -   a projection system (“lens”) PL (e.g. a refractive, catoptric or        catadioptric optical system) for imaging an irradiated portion        of the mask MA onto a target portion C (e.g. comprising one or        more dies) of the substrate W.

As depicted herein, the apparatus is of a transmissive type (i.e., has atransmissive mask). However, in general, it may also be of a reflectivetype, for example (with a reflective mask). Alternatively, the apparatusmay employ another kind of patterning means as an alternative to the useof a mask; examples include a programmable mirror array or LCD matrix.

The source LA (e.g. a mercury lamp or excimer laser) produces a beam ofradiation. This beam is fed into an illumination system (illuminator)IL, either directly or after having traversed conditioning means, suchas a beam expander Ex, for example. The illuminator IL may compriseadjusting means AM for setting the outer and/or inner radial extent(commonly referred to as σ-outer and σ-inner, respectively) of theintensity distribution in the beam. In addition, it will generallycomprise various other components, such as an integrator IN and acondenser CO. In this way, the beam PB impinging on the mask MA has adesired uniformity and intensity distribution in its cross-section.

It should be noted with regard to FIG. 30 that the source LA may bewithin the housing of the lithographic projection apparatus (as is oftenthe case when the source LA is a mercury lamp, for example), but that itmay also be remote from the lithographic projection apparatus, theradiation beam that it produces being led into the apparatus (e.g. withthe aid of suitable directing mirrors); this latter scenario is oftenthe case when the source LA is an excimer laser (e.g. based on KrF, ArFor F₂ lasing). The illumination source intensity may also be made with amirror array or an LCD. The current invention encompasses at least bothof these scenarios.

The beam PB subsequently intercepts the mask MA, which is held on a masktable MT. Having traversed the mask MA, the beam PB passes through thelens PL, which focuses the beam PB onto a target portion C of thesubstrate W. With the aid of the second positioning means (andinterferometric measuring means IF), the substrate table WT can be movedaccurately, e.g. so as to position different target portions C in thepath of the beam PB. Similarly, the first positioning means can be usedto accurately position the mask MA with respect to the path of the beamPB, e.g. after mechanical retrieval of the mask MA from a mask library,or during a scan. In general, movement of the object tables MT, WT willbe realized with the aid of a long-stroke module (coarse positioning)and a short-stroke module (fine positioning), which are not explicitlydepicted in FIG. 27. However, in the case of a wafer stepper (as opposedto a step-and-scan tool) the mask table MT may just be connected to ashort stroke actuator, or may be fixed.

The depicted tool can be used in two different modes:

-   -   In step mode, the mask table MT is kept essentially stationary,        and an entire mask image is projected in one go (i.e., a single        “flash”) onto a target portion C. The substrate table WT is then        shifted in the x and/or y directions so that a different target        portion C can be irradiated by the beam PB;    -   In scan mode, essentially the same scenario applies, except that        a given target portion C is not exposed in a single “flash”.        Instead, the mask table MT is movable in a given direction (the        so-called “scan direction”, e.g. the y direction) with a speed        v, so that the projection beam PB is caused to scan over a mask        image; concurrently, the substrate table WT is simultaneously        moved in the same or opposite direction at a speed V=Mv, in        which M is the magnification of the lens PL (typically, M=¼ or        ⅕). In this manner, a relatively large target portion C can be        exposed, without having to compromise on resolution.

The concepts disclosed herein may simulate or mathematically model anygeneric imaging system for imaging sub wavelength features, and may beespecially useful with emerging imaging technologies capable ofproducing wavelengths of an increasingly smaller size. Emergingtechnologies already in use include EUV (extreme ultra violet)lithography that is capable of producing a 193 nm wavelength with theuse of an ArF laser, and even a 157 nm wavelength with the use of aFluorine laser. Moreover, EUV lithography is capable of producingwavelengths within a range of 20-5 nm by using a synchrotron or byhitting a material (either solid or a plasma) with high energy electronsin order to produce photons within this range. Because most materialsare absorptive within this range, illumination may be produced byreflective mirrors with a multi-stack of Molybdenum and Silicon. Themulti-stack mirror has a 40 layer pairs of Molybdenum and Silicon wherethe thickness of each layer is a quarter wavelength. Even smallerwavelengths may be produced with X-ray lithography. Typically, asynchrotron is used to produce an X-ray wavelength. Since most materialis absorptive at x-ray wavelengths, a thin piece of absorbing materialdefines where features would print (positive resist) or not print(negative resist).

While the concepts disclosed herein may be used for imaging on asubstrate such as a silicon wafer, it shall be understood that thedisclosed concepts may be used with any type of lithographic imagingsystems, e.g., those used for imaging on substrates other than siliconwafers.

Software functionalities of a computer system involve programming,including executable code, may be used to implement the above describedimaging model. The software code is executable by the general-purposecomputer. In operation, the code and possibly the associated datarecords are stored within a general-purpose computer platform. At othertimes, however, the software may be stored at other locations and/ortransported for loading into the appropriate general-purpose computersystems. Hence, the embodiments discussed above involve one or moresoftware products in the form of one or more modules of code carried byat least one machine-readable medium. Execution of such code by aprocessor of the computer system enables the platform to implement thecatalog and/or software downloading functions, in essentially the mannerperformed in the embodiments discussed and illustrated herein.

As used herein, terms such as computer or machine “readable medium”refer to any medium that participates in providing instructions to aprocessor for execution. Such a medium may take many forms, includingbut not limited to, non-volatile media and volatile media. Non-volatilemedia include, for example, optical or magnetic disks, such as any ofthe storage devices in any computer(s) operating as one of the serverplatform, discussed above. Volatile media include dynamic memory, suchas main memory of such a computer platform. Common forms ofcomputer-readable media therefore include, for example: a floppy disk, aflexible disk, hard disk, magnetic tape, any other magnetic medium, aCD-ROM, DVD, any other optical medium, a RAM, a PROM, and EPROM, aFLASH-EPROM, any other memory chip or cartridge, or any other mediumfrom which a computer can read programming code and/or data. Many ofthese forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to a processor forexecution.

As illustrated in FIG. 31, an exemplary mask optimization unit maycontain a processor 1000 which receives input from an input unit 1003.Processor 1000 may be a conventional microprocessor or may be aspecially designed processing unit, such as an EEPROM or EPROM or afabricated integrated circuit. Input 1003 may be any type of electronicinput device, such as a keyboard or a mouse, or may be a memory orinternet connection. Processor 1000 preferably retrieves storedprotocols from ROM 1002 and RAM 1001, such as protocols to implement theprocessing illustrated in FIGS. 2-6, and stores information on RAM 1001.The calculated results of processor 1000 may be displayed on display1004 and may be provided to a mask fabrication unit.

The invention may be embodied in other specific forms without departingfrom the spirit or essential characteristics thereof. The presentembodiments are therefore to be considered in all respects asillustrative and not restrictive, the scope of the invention beingindicated by the appended claims rather than by the foregoingdescription and all changes which come within the meaning and range ofequivalency of the claims are therefore intended to be embraced therein.

What is claimed is:
 1. A method of obtaining a target source and atarget mask comprising the steps of: determining how an illumination isprovided from an illumination source to a plurality of source points anda mask corresponding to a predetermined mask pattern; selectingfragmentation points in an image plane of an image formed by theillumination provided to the predetermined mask pattern; determining anintensity and image log slope of illumination at each fragmentationpoint; and simultaneously changing the intensity and shape of theillumination source and the magnitude and phase of diffraction orders ofthe mask to form an image in the image plane that maximizes the minimumimage log slope at the fragmentation points while forcing the intensityat the fragmentation points to be within a predetermined intensityrange, thereby obtaining the target source and the target mask from thechanged illumination source and mask, respectively.